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# CITATION.cff file created with {cffr} R package
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cff-version: 1.2.0
message: 'To cite package "RtForecastR" in publications use:'
type: software
license: GPL-3.0-only
title: 'RtForecastR: Real-Time Effective Reproduction Number Estimation and Forecasting'
version: 0.1.1
doi: 10.32614/CRAN.package.RtForecastR
abstract: 'Filtered (real-time/causal) and smoothed (retrospective) estimation of
  the time-varying effective reproduction number (Rt) from case-count time series,
  using the EpiFilter algorithm of Parag (2021) <https://doi.org/10.1371/journal.pcbi.1009347>,
  together with a one-step-ahead in-sample prediction check, a genuine out-of-sample
  one-step forecast with predictive intervals, elimination probability P(Rt < 1),
  and forecast calibration metrics (mean absolute error, mean squared error, root
  mean squared error, empirical coverage, and the weighted interval score of Bracher
  et al. (2021) <https://doi.org/10.1371/journal.pcbi.1008618>). Disease-agnostic:
  works for any pathogen given a known generation interval.'
authors:
- family-names: Subedi
  given-names: Raj
  email: rajsubediresearch@gmail.com
repository: https://rajsubediresearch.r-universe.dev
repository-code: https://github.com/rajsubediresearch/RtForecastR
commit: 8b99148c5d124a6604359af48c719c46d7c95cef
url: https://github.com/rajsubediresearch/RtForecastR
date-released: '2026-08-20'
contact:
- family-names: Subedi
  given-names: Raj
  email: rajsubediresearch@gmail.com